solicitation-review-qa

Run eight deterministic QA checks on solicitation review artifacts.

1|2|Updated Apr 1, 2026
One-click install
npx skills add https://github.com/dimagi-internal/ace --skill solicitation-review-qa
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: solicitation-review-qa
Source: https://github.com/dimagi-internal/ace/tree/main/skills/solicitation-review-qa
Command: npx skills add https://github.com/dimagi-internal/ace --skill solicitation-review-qa

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill eliminates the risk of structurally incomplete or malformed solicitation review recommendation and scoring artifacts reaching the human HITL reviewer, which could lead to incorrect, irreversible award_response calls. It catches common structural defects like missing recommendation sections, unnamed awardees, incomplete scoring, unresolved tie-breaks, and premature award claims before human review begins.

Core Features & Use Cases

  • 8 Static, LLM-Free Checks: Runs all validation checks in under 100 milliseconds with no LLM invocation, ensuring fast, deterministic results.
  • Comprehensive Artifact Validation: Verifies the recommendation doc has a required Recommendation section, names a specific awardee, includes substantive reasoning tied to evaluation criteria, and contains no premature award action language.
  • Scoring Rubric Validation: Confirms all submitted responses are scored, the criteria coverage table is populated, the scoring table is well-formed with required columns, and tie-breaks are resolved for close score gaps.
  • Use Case: For ACE Phase 8 solicitation management workflows, run this QA step immediately after the solicitation-review producer generates its artifacts to ensure the human reviewer only sees structurally complete, gradable recommendation documents, reducing post-hoc error correction and rework.

Quick Start

Use the solicitation-review-qa skill to validate the structural correctness of the latest solicitation review recommendation and scoring rubric artifacts before the human reviewer applies the HITL award gate.

Frequently Asked Questions about solicitation-review-qa

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I validate a solicitation review artifact before human award approval?

You validate a solicitation review artifact by running static structural QA checks to catch defects like missing recommendation sections, unnamed awardees, or incomplete scoring before human review. This ensures the reviewer only sees structurally complete documents.

What is pre-award validation for solicitation management workflows?

Pre-award validation is a structural QA step that checks solicitation review and scoring artifacts for completeness and formatting. It gates the irreversible human award decision by returning a binary pass, fail, or incomplete verdict.

How do I check if a scoring rubric is complete and well-formed?

To check if a scoring rubric is complete, verify that all submitted responses are scored, criteria coverage is populated, required table columns exist, and tie-breaks are resolved for close score gaps. This prevents malformed rubrics from blocking reviews.

Does solicitation structural QA require LLM invocation to run checks?

Solicitation structural QA does not require LLM invocation. It runs eight deterministic checks in under 100 milliseconds, validating artifact structure like awardee naming and reasoning quality without language model processing.

What are common structural defects in solicitation review recommendation documents?

Common structural defects include missing recommendation sections, unnamed awardees, incomplete scoring, unresolved tie-breaks, and premature award action language. Static QA checks identify these issues before human review begins.

When should I run static checks on solicitation review artifacts?

Run static checks immediately after the solicitation review producer generates its recommendation and scoring artifacts. This timing ensures the human reviewer only sees structurally complete, gradable documents, reducing post-hoc error correction.